Under-five mortality in the Democratic Republic of the Congo: secondary analyses of survey and conflict data by province

Abstract Objective To compare coverage of key child health policy indicators across provinces and to explore their association with under-five mortality and level of conflict in the Democratic Republic of the Congo. Methods We made a secondary analysis of nationally representative data from 1380 health facilities and 20 792 households in 2017–2018. We analysed provincial-level data on coverage of 23 different indicators for improving common causes of childhood mortality, combined into mean scores for: newborn health, pneumonia, diarrhoea, malaria and safe environment. Using negative binomial regression we compared the scores with provincial-level under-five mortality. With binary logistic regression at the individual level we compared indicators (outcome) with living in a conflict-affected province (exposure). Findings All grouped coverage scores demonstrated large ranges across the 26 provinces: newborn health: 20% to 61%; pneumonia: 26% to 86%; diarrhoea: 25% to 63%; malaria: 22% to 53%; and safe environment: 4% to 53%. The diarrhoea score demonstrated the strongest association with under-five mortality (adjusted coefficient: −0.026; 95% confidence interval: −0.045 to −0.007). Conflict-affected provinces had both the highest as well as the lowest mortality rates and indicator coverages. The odds of coverage were higher in conflict-affected provinces for 13 out of 23 indicators, whereas in provinces unaffected by conflict only one indicator had higher odds of coverage. Conclusion Conflict alone is a poor predictor for child health. Ensuring that children in unaffected provinces are not neglected while addressing the needs of the most vulnerable in conflict settings is important. Prevent, protect and treat strategies for diarrhoeal disease could help improve equity in child survival.


Introduction
The main contributors to mortality in children younger than 5 years in sub-Saharan Africa are lower respiratory infections, diarrhoea, malaria and neonatal conditions, 1 all of which are targeted by evidence-based global action plans. However, the indicators proposed to track progress by these action plans are commonly only reported on a national level, despite over three quarters of variation in under-five mortality in sub-Saharan Africa being explained by subnational factors. 2 The Democratic Republic of the Congo accounts for 291 000 (11%) of the 2 766 000 estimated annual deaths in children younger than 5 years in sub-Saharan Africa. 3 Provincial disparities in under-five mortality have previously been demonstrated, 4 and still persist. 5 Previous studies have shown provincial differences in the prevalence of acute respiratory infections, diarrhoea, fever, malnutrition, vaccination coverage and availability of high-quality obstetric care. [6][7][8][9] However, several of these studies are almost a decade old and only one used the new provincial divisions, 8 as the country transitioned from 11 to 26 provinces in 2015.
Armed conflicts have generally been associated with a high burden of child mortality and morbidity. 10 During the Congolese wars, however, post-neonatal mortality increased but neonatal mortality did not. 11 Additionally, this increased mortality was not found in the post-war period despite the continuing state of conflict. 11 A recent study demonstrated higher odds of delivery in a health facility but lower access to antenatal services for women in high-intensity conflict areas compared with moderate-intensity conflict areas. 12 Several studies have acknowledged higher coverage of health services in the eastern provinces, where the conflict is concentrated, hypothesizing that this is due to support from nongovernmental organizations (NGOs) and the United Nations, with donor funding. 4,13 We aimed to compare the coverage of key policy indicators for better child health across provinces in the Democratic Republic of the Congo and to explore their association with under-five mortality and level of conflict. A subnational perspective should allow for more targeted roll-out of interventions and health-systems planning to support the country in achieving sustainable development goal (SDG) target 3.2 (to end preventable deaths of newborns and children younger than 5 years) in an equitable way.

Study design
We performed a secondary analysis of data from nationally representative, cross-sectional surveys of health facilities and households in the Democratic Republic of the Congo in 2017-2018. The framework for the study was based on a Table 1

Setting
The Democratic Republic of the Congo has an estimated population of 85-100 million 14,15 residing across 26 provinces and 516 health zones. 16 Health care is offered by public and private operators including faith-based organizations. 16 In addition, several NGOs and international organizations operate in the country. 17 An estimated 40% of the country's health-care spending comes from out-of-pocket expenditure, with international donors providing a similar proportion. 18 Ethical approval for the study was obtained from the Swedish Ethical Review Authority (Dnr 2020-05190).

Data sources
Data collection and sampling procedures for the data sets have been described elsewhere. 5,19,20 We describe here some important details about the data sets; further details are in the supplementary files in the authors' data repository. 21 We obtained data on health indicators and socioeconomic status from two national data sets. The Service and Provision Assessment 2017-2018 19 used stratified random probability sampling to select 1412 health facilities from a list of all 12 050 operational health facilities, excluding health posts. These facilities were surveyed between October 2017 and April 2018. Of the sampled health facilities, 32 (2.3%) were not surveyed, mainly due to security problems. We extracted data from the inventory section of the data (for example, on medications and equipment), and from the service provider questionnaire (for example on receipt of training in kangaroo mother care).
The Multiple Cluster Indicator Survey 2018 household survey 5 was designed to provide provincial estimates based on individual-level data using a sample frame based on the 1984 population census. A systematic random sample of 30 households was drawn from each of the 721 clusters giving an overall sample of 21 630 households, of which 20 792 (96.1%) were successfully interviewed between December 2017 and July 2018. Twelve clusters were not visited due to insecurity problems, mainly in Tanganyika and Maniema provinces. We used data from the questionnaires about the household, women and children younger than 5 years. We extracted data on relative socioeconomic status (continuous variable) based on household asset ownership and urban or rural setting.
To obtain data on areas of conflict in the Democratic Republic of the Congo we used a third data set. The Uppsala Conflict Data Program Georeferenced Event Data Set contains global temporally and spatially disaggregated data of conflict events. [22][23][24][25] For an event to be included it must have resulted in at least one death and the actor involved must have been involved in events that together accumulated to at least 25 deaths in one calendar year. We calculated annual levels of conflict for each province between 2013-2018 to match the time frame used to calculate the under-five mortality. We divided provinces into three different conflict categories, adapting the definition from Uppsala University regarding state-based violence: major conflict (if more than 1000 battlerelated deaths had occurred in one of the calendar years), minor conflict (more than 25 battle-related deaths) and no conflict (25 deaths or fewer). 26

Data collection
We compiled a list of 47 key policy indicators for action on common causes of childhood mortality from the following documents: (i) Every Newborn action plan; 27,28 (ii) Global Action Plan for the Prevention and Control of Pneumonia and Diarrhoea; 29 and (iii) Global Technical Strategy for Malaria 2016-2030. 30 We reviewed the national health facility and household surveys for available data on coverage of the identified indicators. We used data on 23 different indicators: 10 of the 15 indicators in the Every Newborn action plan, 27 (Table 1). We excluded indicators if no data were available, the intervention was not implemented at the time of the survey, the indicator was not focused on the child (maternal indicators, for example) or too few observations were recorded. Details about the excluded indicators are in the supplementary files. 32 We set the target coverage at 80% for all indicators, except exclusive breastfeed-ing (50%) and caesarean section (10%), using the district-level targets set out by the Global Action Plan for the Prevention and Control of Pneumonia and Diarrhoea and the International Vaccine Access Centre. 31 We calculated the indicators according to the definitions on Table 1; some indicators were identical to the source reports whereas other differed in definition and were not reported in the reports. We then combined data for the available indicators into six grouped coverage scores covering common causes of childhood mortality, using the same method as the International Vaccine Access Center: 31 (i) newborn health (using indicators from the Every Newborn action plan); (ii) pneumonia; (iii) diarrhoea; (iv) combined pneumonia and diarrhoea (each from the Global Action Plan for the Prevention and Control of Pneumonia and Diarrhoea); (v) malaria (from the Global Technical Strategy for Malaria 2016-2030); and (vi) safe environment. We generated overall grouped scores by adding the coverage for all included indicators and dividing by the number of indicators in each group (Box 1).

Data analysis
Our primary outcome was provinciallevel under-five mortality, calculated using the synthetic cohort probability method. 33 We collapsed the indicator variables to provincial means and summed these into the six indicator grouped scores (Box 1) as the main exposure variables. We applied sample weights to adjust for sampling method for all data taken from the health facility and household data sets. All numerators and denominators presented here are raw data whereas some percentages are weighted. We performed negative binomial regression (due to overdispersion in the data), to estimate the associations between provincial-level under-five mortality and indicator coverage scores for both grouped and individual indicators. Due to collinearity, we analysed each indicator separately.
We adjusted the negative binomial regressions for provincial level of conflict (none, minor or major conflict) and socioeconomic status, reporting the results as an adjusted coefficient. Due to low levels of missing data, we performed a complete case analysis. Differences in mean scores were compared using twosample t-tests.

Research
Child health indicators and conflict, Democratic Republic of the Congo Mattias Schedwin et al.
We performed an individual-level analysis using logistic regression, to explore associations between being covered by an indicator (outcome) and living in a conflict-affected province (exposure), combining major and minor levels of conflict. We adjusted the analysis for household socioeconomic status. The analysis was performed using Stata version 16 (StataCorp, College Station, Texas, United States of America).

Results
Overall, there were 1209 under-five deaths among 21 741 reported births. Under-five mortality, socioeconomic status and level of conflict varied considerably across provinces (Fig. 1). Mean provincial socioeconomic status was not significantly associated with under-five mortality (P = 0.132). The highest under-five mortality was found in Kasaï (169 deaths per 1000 live births; 95% confidence interval, CI: 134 to 204) and the lowest in North Kivu (26 deaths per 1000 live births; 95% CI: 10 to 42). There were 14 out of 26 provinces classified as conflict-affected, of which three were major conflicts (North Kivu, Kasaï and Kasaï-Central provinces). There were 696 under-five deaths out of the 11 796 reported births among women interviewed in conflict provinces compared with 513 deaths out of 9945 births in non-conflict provinces.

Indicator coverage
Each indicator showed a considerable range in coverage, with chlorhexidine cord-cleansing having the widest range from 2% in Mongala (6/40 facilities) to 89% in South Kivu (50/59 facilities), followed by pneumococcal conjugate vaccination coverage, ranging from 9% in Sankuru (14/193 facilities) to 90% in North Kivu (129/170 facilities); full data are in the supplementary files. 32 The target coverage was met on the national level for one indicator, exclusive breastfeeding (median: 54.8%; interquartile range, IQR: 44.6-66.4). However, at the subnational level the target was only met for 16 out of 26 provinces (Table 2). For nine of the 23 indicators, at least one province reached the target coverage. Access to clean fuel for cooking had the lowest coverage at 0% in 16 out of 26 provinces (median: 0.1%; IQR: 0.0 to 0.8), followed by caesarean section (median: 1.8%; IQR: 0.9 to 6.0), access to hand-washing with soap (median: 7.3%; IQR: 3.5 to 17.5) and kangaroo mother care (median: 8.1%; IQR: 4.0 to 16.2).

Associations with mortality
Among the overall grouped scores, the diarrhoea score (adjusted coefficient: −0.026; 95% CI: −0.045 to −0.007) and the combined pneumonia and diarrhoea score (adjusted coefficient: −0.019; 95% CI: −0.039 to −0.000) were the only groups with a significant association with under-five mortality; a one-point increase in score resulted in 2.6% and 1.9% fewer deaths per 1000 live births, respectively (Table 4).
Among the individual indicators for newborn health, caesarean section (adjusted coefficient: −0.083; 95% CI: −0.130 to −0.037) and exclusive breastfeeding (adjusted coefficient: −0.012; 95% CI: −0.022 to −0.001) were significantly associated with decreased underfive mortality (see data repository). 32 Newborn resuscitation was positively associated with under-five mortality (adjusted coefficient: 0.015; 95% CI: 0.002 to 0.028). Kangaroo mother care (adjusted coefficient: −0.021; 95% CI: −0.043 to 0.001) showed a strong association with mortality but did not meet the significance level. For safe environment indicators, handwashing with soap showed a strong protective association with mortality and was the

Malaria score
Numerator: insecticide-treated net, malaria testing, first-line malaria treatment Denominator: number of indicators (3)

Safe environment score
Numerator: access to improved drinking-water, access to handwashing with soap, access to an improved sanitation facility, access to clean fuel for cooking Denominator: number of indicators (4) a We did not include pneumonia care-seeking, pneumonia treatment and rotavirus vaccine coverage due to lack of data.

Research
Child health indicators and conflict, Democratic Republic of the Congo Mattias Schedwin et al.

Associations with conflict
Summing the calculated under-five mortality rates for each province divided by the number of provinces, we found that under-five mortality was higher, but not statistically different, in conflict-affected provinces (74 per 1000 live births) compared with provinces unaffected by conflict (71 per 1000 live births, P = 0.798).
For 13 out of 23 indicators the odds of coverage of the indicator were higher in conflict-affected provinces. In contrast, only one indicator (sleeping under an insecticide-treated bed net) had higher odds of coverage in a province unaffected by conflict (

Discussion
In our analysis of nationally representative household and facility surveys, we found that target coverage for 14 out of 23 key child health indicators had not been achieved in any province of the Democratic Republic of the Congo. Several of the indicators with the lowest coverage were related to diarrhoea, which also had some of the strongest associations with under-five mortality. Overall, conflict-affected provinces had higher coverage of almost all grouped indicator scores; however, mortality was higher, but not significantly so, in these provinces.
The grouped score for diarrhoea indicators demonstrated the strongest association with under-five mortality,   and large disparities in this score were seen across provinces. Diarrhoeal disease remains one of the biggest contributors to under-five mortality, estimated to account for 8% (480 000 deaths) of the 5 300 000 deaths globally 34 and reported as 9% in the Democratic Republic of the Congo. 35 Universal coverage with oral rehydration solutions could prevent up to 93% of diarrhoea-related deaths, 36 but global coverage has remained low at about 42%. 37,38 Major improvements can be achieved through increased knowledge about diarrhoea symptoms, availability of oral rehydration solutions and well-trained health-care workers who promote their use. 39 For the Democratic Republic of the Congo, an important milestone in reducing diarrhoeal disease was the introduction of rotavirus vaccine in 2019, which was not included in our analysis (national coverage was 33% in 2020). 40 Our results suggest the importance of accelerating access to safe water and sanitation if SDG targets are to be achieved. Access to handwashing with soap had a protec-tive association with under-five mortality in our study and the widest range of coverage between provinces (from 0.5% to 70%). Focusing on relatively low-cost interventions around access to oral rehydration solutions, alongside water, sanitation and hygiene initiatives and equitable vaccine access, could be particularly effective, especially given the country's high burden of cholera. 41 Among the neonatal indicators, caesarean section and kangaroo mother care coverage showed the strongest association with under-five mortality. Caesarean section likely reflects the availability of higher-level functional care, but this result should also be interpreted with caution since there are no suggested positive effects on health outcomes with caesarean section rates above 10%. 42 Kangaroo mother care on the other hand is low-cost and one of the most effective interventions to prevent deaths in low-birth-weight infants. 43 However, the indicator used in this study showed a low coverage (median 8%, range 0-32%) leaving much room for improvement. Interestingly, researchers found that the quality of maternal and newborn care in North Kivu was low. 44 In our analysis, however, it was one of the best-performing provinces suggesting that quality improvements are still needed, even when indicator coverage targets are met. Globally, low quality of care is a bigger contributor to mortality than access. 45 The Democratic Republic of the Congo struggles with medical educational institutions of inadequate quality, a lack of qualified health personnel in general, and a concentration of trained health personnel in the major cities, making high-quality health care challenging. 16 Poverty and inadequate funding of the health-care sector further complicates accessibility and quality. 16 Our individual-level analysis showed higher odds of being covered by a policy indicator if the child lived in a conflict-affected province than a province unaffected by conflict. Children in conflict-affected provinces had around double the odds of being covered by several of the water, sanitation and hygiene, vaccination and health-facility indicators. It may be that with longlasting humanitarian needs and conflict events there is a risk of provinces not affected by conflict being neglected, although this possibility was not raised in the Lancet Series on Women's and Children's Health In Conflict Settings. 10 As an example, South Kivu had the bestfunded health system in the Democratic Republic of the Congo in 2012, when taking humanitarian aid into account. 46 In contrast, mortality was marginally higher in the conflict-affected provinces, although large disparities in mortality were found between conflict-affected provinces. North Kivu had the lowest under-five mortality, highest indicator coverage, and belonged to the highest quartile for socioeconomic status. However, the complete opposite was observed for Kasaï, suggesting that conflict might not be a good predictor of child health or health needs. North Kivu has been affected by conflict since the 1990s, and has a large humanitarian presence, 47 as compared with Kasaï, which experienced an intense but relatively short conflict episode in the years before data collection. Eastern Democratic Republic of the Congo is also rich in natural resources and has access to cross-border trade, providing the prerequisites for a larger economy that could be a contributor to the higher coverage observed. If targets are to be reached equitably, it is necessary to ensure that well-established patterns of delivering aid do not get in the way of reaching the most vulnerable people. 48 Our analysis can only report associations, not causation, and therefore it is important that the underlying causes of these disparities are understood and addressed. Furthermore, our provincial analysis does not provide insights into the subprovincial disparities or the children living closest to conflict. 10  Tanganyika  66  Minor  Q3  26  29  35  31  35  19  Kwilu  71  No  Q3  30  29  33  32  35  7  Kongo Central  77  Minor  Q4  46  54  67  46  38  16  Lomami  78  Minor  Q1  41  37  45  37  29  10  Kasaï-Oriental  82  Minor  Q2  40  39  45  37  25  24  Maniema  91  Minor  Q2  34  29  27  39  35  4  Haut-Katanga  98  Minor  Q4  47  42  60  33  43  28  Kasaï-Central  100  Major  Q2  43  44  59  38  34  6  Sud-Ubangi  101  No  Q2  43  40  48  42  53  24  Tshuapa  101  No  Q1  22  28  33  30  32  6  Sankuru  127  No  Q1  36  25  27  33  24  6  Haut Lomami  131  No  Q3  38  42  46  38  41  19  Kasaï  169  Major  Q1  29  24  26  25  23  4  Overall  70  NA  NA  38  38  45  38  35  17 NA: not applicable. a Major conflict: more than 1000 battle-related deaths occurring in one of the calendar years; minor conflict: more than 25 battle-related deaths; no conflict: 25 deaths or fewer. 32 b The wealth index is a composite indicator, ranking all included households, using information on ownership of consumer goods and rural/urban status. The wealth index has here been divided into the following wealth quartiles, Q1: 0-25%, Q2: 25-50%, Q3: 50-75%, Q4: 75-100%. Note: We calculated grouped indicator scores by summing the coverage for each indicator divided by the total number of indicators in the group. n is the number of indicators in the group. See Box1 for the included indicators. Provinces are sorted from low to high under-five mortality. Data for each individual indicator are in the supplementary files. 21 Child health indicators and conflict, Democratic Republic of the Congo Mattias Schedwin et al.

Under-five mortality C onflict Wealth index
The study had some limitations. First, the ecological approach used for this study only allows for crude analysis and may be limited due to the low number of observations; however, our aim was to give a broad overview of coverage and importance for key child health indicators. The indicators are global targets and, in many ways, act as proxies for a functioning society, infrastructure, health-care systems and political systems. Nonetheless, the strongest associations should be interpreted as potential best-buy interventions to target nationally with a particular focus on the provinces with the lowest coverage. Increasing coverage requires efforts across many sectors, targeting determinants outside the health sector such as poverty, education, food security and good governance, 49 besides well-trained health-care workers, and increased access to equipment, medication and vaccination, 50 which are all challenges for the Democratic Republic of the Congo today.
Second, even though Multiple Cluster Indicator Survey data completion rates for major-conflict provinces were high 21 , and the report does not mention any purposeful exclusions due to insecurity, households and facilities in the most insecure areas are likely to have been excluded. The same is likely for households far away from the main roads in the poorest provinces with limited infrastructure. We tried to account for these effects by adjusting for provincial socioeconomic status and conflict level. Additionally, the data do not include children in camps for internally displaced persons or refugees, who constitute a considerable number of children in the Democratic Republic of the Congo. 51 Third, the sample size did not allow for provincial analysis of all variables, such as care-seeking and treatment for pneumonia. This issue highlights the need for more robust provincial monitoring and evaluation data systems, to improve tracking and data quality. We should also stress that we used multiple hypothesis testing which increases the risk of finding significance by chance.
Finally, categorizing provinces by conflict intensity level comes with many challenges and, as with any classification approach, important nuances will be missed. Furthermore, the Uppsala University conflict intensity level is intended for state-based violence, whereas we

Province
Newborn health score a

No conflict C onflict
Pneumonia score Malaria score Combined pneumonia and diarrhoea score a Diarrhoea score Safe environment score * * * a Statistically significant difference (P < 0.05) with two-sample t-test. Notes: Conflict: more than 25 battle-related deaths; no conflict: 25 deaths or fewer. 32 The boxes in the whisker box plot represent the interquartile range, the whiskers are values within 1.5 times the distance of the interquartile range starting from the limit of the box and the dots are scores further than 1.5 interquartile range from the box limit.
Conclusión El conflicto por sí solo no es un buen factor de predicción de la salud infantil. Es importante asegurar que los niños de las provincias no afectadas no sean desatendidos mientras se atienden las necesidades de los más vulnerables en las situaciones de conflicto. Las estrategias de prevención, protección y tratamiento de las enfermedades diarreicas podrían contribuir a mejorar la equidad en la supervivencia infantil.